Campus Units

Center for Statistics and Applications in Forensic Evidence (CSAFE)", Statistics

Document Type

Article

Publication Version

Published Version

Publication Date

4-1-2019

Journal or Book Title

Significance

Volume

16

Issue

2

First Page

29

Last Page

35

DOI

10.1111/j.1740-9713.2019.01252.x

Abstract

The 2009 National Academy of Sciences report found pattern‐evidence disciplines to be rife with subjectivity. In the decade since, machine learning methods have been developed to try to address that issue. By Alicia Carriquiry, Heike Hofmann, Xiao Hui Tai and Susan VanderPlas.

Comments

This following article is published as Carriquiry, Alicia, Heike Hofmann, Xiao Hui Tai, and Susan VanderPlas. "Machine learning in forensic applications." Significance 16, no. 2 (2019): 29-35. Posted with permission of CSAFE.

Copyright Owner

The Royal Statistical Society

Language

en

File Format

application/pdf

Included in

Legal Studies Commons

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